Flitch tracking

ABSTRACT

In various embodiments, a scanner optimizer system may generate a virtual model of a predicted flitch based on a 3D model of a log/cant and a cut solution for the log/cant. The scanner optimizer system may compare a virtual model of an actual flitch to virtual models of predicted flitches by comparing data points at a fixed elevation relative to one or both faces of the models. Based on the comparisons, the scanner optimizer system may identify the source log from which the actual flitch was cut. In addition, the scanner optimizer system may identify the saw used to cut the actual flitch, and/or other relevant information, and use the additional information to monitor and adjust the saws and other equipment. Embodiments of corresponding apparatuses and methods are also described.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/907,257 filed Feb. 27, 2018, which claims the benefit of U.S.Provisional Patent Application No. 62/464,343 filed Feb. 27, 2017, bothtitled “Flitch Tracking,” the disclosures of which are herebyincorporated in their entirety.

TECHNICAL FIELD

Embodiments disclosed herein relate to lumber processing, and morespecifically to quality and processing control in lumber processingfacilities.

BACKGROUND

Lumber mills process logs in a variety of ways to produce lumber. Acommon strategy is to cut the logs into several pieces, such as flitchesand/or cants, which can then be cut into lumber of the desireddimensions. For example, some mills open flat faces along opposite sidesof the log and cut one or more flitches from each side of the resultingcant. The flitches are sent to an edger to be cut into side boards. Theremaining portion of the two-sided cant is chipped or cut to yield asmaller four-sided cant, which is sent to a gang saw to be cut intocenter boards. Some of the other options include cutting at least oneflitch from each side, cutting multiple flitches from multiple sides,cutting the entire two-sided cant into flitches, or cutting a flitchfrom one side of the log before rotating the log 90 degrees and cuttinga flitch from the next side.

The flitches are dropped onto a queuing deck to be picked up by anunscrambler, which singulates the flitches. The singulated flitches arefed onto a lugged conveyor and conveyed through a scan zone to an edgerinfeed. The flitches are positioned on the edger infeed for cutting andconveyed into the edger to be cut into boards. The cant is sent to agang saw to be cut into additional boards.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments will be readily understood by the following detaileddescription in conjunction with the accompanying drawings. Embodimentsare illustrated by way of example and not by way of limitation in thefigures of the accompanying drawings.

FIG. 1 is a schematic diagram of a lumber processing system;

FIG. 2 is a schematic side elevational view of a primary breakdown lineand corresponding operations;

FIGS. 3A-3E illustrate examples of sensor arrangements for a first scanzone, or sub-zones thereof, along a primary breakdown line;

FIGS. 4A-4B illustrate examples of sensor arrangements for a second scanzone, or subzones thereof, along a secondary breakdown line;

FIG. 5 is a flow diagram of a method of matching flitches to a sourcelog/cant;

FIG. 6 is a flow diagram of a method of generating a virtual model of alog;

FIG. 7 is a flow diagram of a method of generating a virtual model of apredicted flitch;

FIG. 8 is a flow diagram of a method of generating a virtual model of anactual flitch;

FIG. 9 is a flow diagram of a method of matching virtual models ofactual flitches to virtual models of predicted flitches;

FIG. 10 is a flow diagram of a method of comparing virtual models ofactual flitches to virtual models of predicted flitches;

FIG. 11 illustrates an example of a topological virtual model; and

FIG. 12 is a flow diagram of a method of monitoring the performance of alumber processing system;

FIG. 13 illustrates an example of a computer system suitable forpracticing embodiments of the present disclosure; and

FIGS. 14-17 illustrate examples of user interface screens, all inaccordance with various embodiments.

DETAILED DESCRIPTION OF DISCLOSED EMBODIMENTS

In the following detailed description, reference is made to theaccompanying drawings which form a part hereof, and in which are shownby way of illustration embodiments that may be practiced. It is to beunderstood that other embodiments may be utilized and structural orlogical changes may be made without departing from the scope. Therefore,the following detailed description is not to be taken in a limitingsense, and the scope of embodiments is defined by the appended claimsand their equivalents.

Various operations may be described as multiple discrete operations inturn, in a manner that may be helpful in understanding embodiments;however, the order of description should not be construed to imply thatthese operations are order dependent.

The description may use perspective-based descriptions such as up/down,back/front, and top/bottom. Such descriptions are merely used tofacilitate the discussion and are not intended to restrict theapplication of disclosed embodiments.

The terms “coupled” and “connected,” along with their derivatives, maybe used. It should be understood that these terms are not intended assynonyms for each other. Rather, in particular embodiments, “connected”may be used to indicate that two or more elements are in direct physicalor electrical contact with each other. “Coupled” may mean that two ormore elements are in direct physical or electrical contact. However,“coupled” may also mean that two or more elements are not in directcontact with each other, but yet still cooperate or interact with eachother.

For the purposes of the description, a phrase in the form “A/B” or inthe form “A and/or B” means (A), (B), or (A and B). For the purposes ofthe description, a phrase in the form “at least one of A, B, and C”means (A), (B), (C), (A and B), (A and C), (B and C), or (A, B and C).For the purposes of the description, a phrase in the form “(A)B” means(B) or (AB) that is, A is an optional element.

The description may use the terms “embodiment” or “embodiments,” whichmay each refer to one or more of the same or different embodiments.Furthermore, the terms “comprising,” “including,” “having,” and thelike, as used with respect to embodiments, are synonymous.

As used herein, a “cant” is a portion of a log that is formed bychipping or sawing along at least one side of the log to form asubstantially flat face along the side of the log. As used herein, a“flitch” is a piece of wood that has a pair of machined opposing facesjoined by two edges, at least one of which is a wane edge. For example,a flitch may be formed by cutting through a cant lengthwise, generallyparallel to a machined face of the cant, to sever the flitch from aremaining portion of the cant.

In exemplary embodiments, a computer system may be endowed with one ormore components of the disclosed apparatuses and/or systems, and may beemployed to perform one or more methods, as disclosed herein.Functions/processes attributed in the following description to aparticular computer system may instead be performed by another computersystem, or distributed among two or more computer systems. Likewise,functions/processes attributed to multiple computer systems may beperformed by a single computer system.

As flitches are cut from logs/cants, they typically drop onto thequeuing deck in the order in which they were sawn. However, the flitchescan stack up randomly on the queuing deck and/or be picked up out oforder by the unscrambler, which causes them to be out of order when theyreach the edger scan zone. As a result, the flitches cannot be matchedto their source logs based solely on their order of arrival at theedger. This means that the saw(s) that cut a particular flitch cannot beidentified after the flitch has been dropped onto the queuing deck. Ifthe facility is consistently producing some flitches that are too thinor too thick, identifying the problem saw(s) can be very difficult andtime-consuming.

In most facilities that use log scanner/optimizers and flitchscanner/optimizers, the flitches are typically scanned at higherresolution than the logs. Therefore, if the flitches can be matched tothe saws that cut them, the information generated by the existing flitchscanner can be used to assess the performance of the saws. Embodimentsof systems, apparatuses and methods described herein may enable afacility to identify a primary workpiece (e.g., a log or a cant), andthe zone or portion thereof, from which a flitch was cut. Suchembodiments may further enable the facility to use the data collected bysensors upstream of the edger (e.g., an existing flitch scanner) toidentify the saw(s) that cut a particular flitch and monitor theperformance of the saws. In some embodiments, the saws and/or otherequipment (e.g., sensors, chipper, etc.) may be adjusted based on theperformance information.

In addition, some sawmills process logs of different tree species, andthe value of a given cut pattern may be different for one species thanfor another. For example, the most profitable cut pattern for a log ofone species may be different than the most profitable cut pattern foranother log of identical dimensions, but of a different species.Therefore, some sawmills may sort the logs into batches according tospecies and process each batch separately. However, the sorting mayincrease the overall cost of operation and thereby reduce profits.Identifying the wood species of the flitches upstream of the edger mayallow the sawmill to cut each flitch according to the most profitablecut pattern for that flitch while processing logs of multiple species.

In various embodiments, a lumber processing system may include a primarybreakdown line, a secondary breakdown line, and a scanner optimizersystem.

The primary breakdown line may include one or more cutting devices(e.g., chippers, profilers, and/or saws) and a first transport system.The secondary breakdown line may include an edger and/or trimmer and asecond transport system. Flitches may be cut from logs along the primarybreakdown line and edged into boards along the secondary breakdown line.

The scanner optimizer system may include a first plurality of geometric(e.g., laser profile) sensors arranged to form a first scan zone alongthe first transport system, a first computer system operatively coupledwith the first plurality of sensors, a second plurality of geometric(e.g., laser profile) sensors arranged to form a second scan zone alongthe second transport system, and a second computer system operativelycoupled with the second plurality of sensors. Optionally, the scanneroptimizer system may further include a third computer system incommunication with the first and second computer systems.

The first computer system and associated sensors may detect thegeometric profile of a log, generate a 3D virtual model of the log basedon the geometric profile, and determine an optimized cut solution forthe log based on the virtual model. Implementing the cut solution mayinvolve chipping or sawing a flat face along the log and cuttinglongitudinally through the log (now a cant) parallel to the chipped faceto release a flitch from the remaining center cant. The optimized cutsolution may define predicted cut lines along which the log is to be cutinto predicted products, including a predicted flitch. In someembodiments the first computer system may determine a saw set (i.e.,instructions for positioning the corresponding chipper/saw(s) to cut thelog/cant according to the cut solution), in which case the saw set maybe considered part of the optimized cut solution. Optionally, thepredicted cut lines may be defined by the saw set. The first computersystem and/or associated sensors may send the 3D virtual model of thelog and the optimized cut solution to the third computer system, and thethird computer system may use the information to generate a 3D virtualmodel of the predicted flitch.

The log may be cut according to the optimized cut pattern to obtain theflitch. The second computer system and associated sensors may detect thegeometric profile of the actual flitch upstream of the edger, generate a3D virtual model of the actual flitch based at least on the geometricprofile, and determine an optimized cut solution for the flitch based atleast on the 3D virtual model. The second computer system and/orassociated sensors may send the 3D virtual model of the actual flitch tothe third computer system.

In various embodiments, some or all of the 3D virtual models may begeometric surface models of the logs/flitches. For example, the log orflitch may be modeled as a set of cross sections at fixed intervalsalong the length (Z axis) of the log or flitch, with each of the crosssections represented by a corresponding set of data points. The datapoints may be two-dimensional points (X and Y) that represent the outersurface at that Z location, such that the data points collectivelydefine the shape of the outer surface of the log or flitch.

In some embodiments, a log record may be generated for each log andplaced in a queue, and each computer system may associate the data itgenerates/receives with the corresponding log record. A log record mayinclude data such as the virtual model of the log, the corresponding cutsolution, 2D/3D virtual models of predicted flitches, and thecorresponding cut zones of the log. Other relevant information (e.g.,log/tree species, ID number of the log/flitch, location/size/type ofdefects, length, diameter, sweep, and/or other characteristics) may alsobe associated with corresponding log records in the queue. In someembodiments, a log record may be created by the first computer systemfor each log (e.g., in response to receiving the next set of scan datafrom the first scan zone or sub-zone thereof).

In some embodiments, the third computer system may be configured togenerate 2D virtual models of the predicted flitches and the actualflitches based on the 3D virtual models of the predicted and actualflitches. Optionally, some or all of the 2D virtual models may be‘topographical’ models. A topographical model may represent the outercontour of the actual or predicted flitch within a plane that isparallel to, and at a known distance from, one or both of the facesdefined in the 3D virtual model. For example, if the 3D virtual modelincludes a plurality of data points that collectively define the outershape of a flitch, the corresponding topographical model may be thesubset of those data points that lie within a reference plane at a knowndistance from one or both faces (e.g., equidistant between the faces).Alternatively, some or all of the data points of the topographical modelmay be extrapolated from the data points of the 3D virtual model (e.g.,if few or none of the data points of the 3D model are within the desiredreference plane). The location of the reference plane relative to theface(s) may be constant, such that each topographical model representsan outer contour at the same elevation.

The third computer system may compare each 2D virtual model of an actualflitch to 2D virtual models of predicted flitches associated with logrecords in the queue, and identify a match based on the comparisons. Thethird computer system may record the match in the respective log recordto identify the log and zone thereof from which the flitch was cut.

In some embodiments, the third computer system and/or other computersystem(s) may be configured to analyze the model and/or match data toobtain information about predicted and actual outcomes of logprocessing. The information may be used to evaluate the positioning andperformance of the cutting devices, scanners, and/or other equipment.For example, in some embodiments the information may be used to assessthe calibration of cutting devices or sensors, identify positioning orcutting errors such as misalignments or saw snaking, and identify thesource of the error.

In various embodiments, a conventional lumber processing system may beupgraded by programming one or more of the system's existing scanneroptimizer systems to perform methods described herein, and/or by addingadditional computers/sensors programmed to perform the methods. Forexample, an existing lumber processing system may include an existinglog optimizer and an existing edger optimizer programmed to perform mostor all of the operations attributed herein to the first and secondcomputers, and the existing system may be modified by adding a thirdcomputer system programmed to perform the remaining operations, and/orby programming one or more of the existing computer systems to performthe remaining operations.

Turning now to the figures, a schematic diagram of a lumber processingsystem 100 is illustrated by way of example in FIG. 1, in accordancewith various embodiments. Lumber processing system 100 may include aprimary breakdown line 100 a and a secondary breakdown line 100 b.

The primary breakdown line 100 a may include a log turner 110, a chipper112, saws 116, and a transport system 108 configured to convey logs 10and cants 12 (and optionally, center cants 14) along a path of flow thatextends through the log turner and the cutting devices. Alternatively,the primary breakdown line may have a saw center (e.g., one or more bandsaws or paired circular saws) upstream of saws 116 instead of a chipper.

Transport system 108 may include any suitable number and combination oftransfers, conveyors, and/or positioning devices (e.g., feed rolls,positioning pins/rolls, hold down rolls, lifts, skids/pans, ramps,etc.). In some embodiments transport system 108 may include a series ofconveyors that collectively define the path of flow through the logturner, chipper, and saw. For example, the transport system may includea flighted chain conveyor that transports logs to the log turner, asharp chain conveyor that transports the logs into/through chipper 112,and another conveyor and/or paired feed rolls that feed the resultingcants into saws 116. In some embodiments portions of the transportsystem such as feed rolls and conveyors may be selectively operable toskew and/or slew the logs or cants as they are being fed into or througha corresponding machine center. Alternatively, the feed rolls and/orconveyors may be fixed in position and the machine centers or partsthereof (e.g., saws, chip heads) may be selectively repositionable. Asanother alternative, a conveyor and a corresponding machine center maybe selectively repositionable. The number and arrangement of conveyors,feed/positioning rolls, hold down rolls, and other such components mayvary among embodiments.

Log turner 110, chipper 112, and saws 116 may be conventional devices ofany suitable number and configuration. For example, log turner 110 maybe a roll-type, ring-type, sharp chain-type, rotary, knuckle, or othertype of log turner. Chipper 112 may have one or more conical,drum-style, or other type of chip heads. Optionally, chipper 112 may bea chipper-canter (e.g., a vee chipper-canter, horizontal chipper-canter,or vertical chipper-canter). Saws 116 may include one or more band sawsand/or circular saws. For example, saws 116 may be a quad bandmill or aquad arbor saw.

Optionally, the primary breakdown line 100 a may further includeadditional handling or positioning devices. Examples of such devicesinclude (but are not limited to) log loaders, debarkers, log kickers,cant turners/kickers, positioning/feed rolls, hold down rolls, and liftpans/skids. The number, arrangement, type, and configuration of suchdevices may vary among embodiments.

In various embodiments, the secondary breakdown line 100 b may includean edger infeed 122, an edger 130, and a transport system 118 configuredto convey flitches from transport system 108 to edger infeed 122.

Again, transport system 118 may be a conventional conveyor/transfersystem. Transport system 118 may include any suitable number and type(s)of transfers, conveyors, positioning devices, and the like. Optionally,transport system 118 may include several transfers/conveyors arranged insequence. For example, in some embodiments transport system 118 mayinclude a queuing deck, an unscrambler downstream of the queuing deck,and a lugged chain conveyor between the unscrambler and the edgerinfeed. Optionally, a lug loader and/or lumber indexing devices such asduckers, pins/stops, or other such devices may be provided between theunscrambler and the lugged chain conveyor to deal the flitches intocorresponding lug spaces.

Edger infeed 122 may be a conventional edger infeed. Edger infeed 122may include one or more conveyors operable to move the flitches into theedger. Optionally, edger infeed 122 may further include hold-down rollsabove the conveyor(s). In some embodiments transport system 118 and/oredger infeed 122 may further include a positioning system selectivelyoperable to place the flitches onto the edger infeed 122 in desiredpositions for cutting. For example, the positioning system may includepins or conveyors that are independently operable to position theflitches onto the ramps, and the ramps may be operable to lower therepositioned flitches onto the edger infeed 122. In various embodiments,transport system 118 and/or edger infeed 122 may further include variousother devices such as ending rolls, board/flitch turners, wane sensors,duckers/stops, drop-out gates, and the like.

Edger 130 may be a straight-sawing, curve-sawing, gang, or other type ofedger. Regardless, edger 130 may be a conventional edger, with one ormore saws operable to cut flitches into boards. Optionally, edger 130may also include side chippers, a reman head, and/or other features inany suitable number, type, and arrangement.

The scanner optimizer system may include a first group of sensors 102and a second group of sensors 120 arranged to form corresponding scanzones along the primary and secondary breakdown lines, respectively.

Sensors 102 may be arranged to form a first scan zone along transportsystem 108. In some embodiments, the first scan zone may be locatedupstream of the log turner 110. In other embodiments, sensors 102 may bearranged to form the first scan zone between the chipper 112 and thesaws 116. In still other embodiments, the first scan zone may includemultiple sub-zones formed by corresponding groups of sensors 102. Forexample, as illustrated in FIG. 1, groups of sensors 102 may be arrangedto form corresponding sub-zones upstream and/or downstream of the logturner 110, between the chipper 112 and saws 116, and downstream of saws116. The location and number of sub-zones may vary among embodiments.Optionally, sensors 102 may be arranged at intervals and used to scancorresponding portions of the workpiece to thereby increase the speed atwhich scan data is captured from the primary workpiece. Alternatively,sub-zones may be arranged at different locations to scan primaryworkpieces at different phases of processing (e.g., before rotation,after rotation but prior to chipping, after chipping but prior tosawing, and/or after sawing).

Sensors 120 may be arranged to form a second scan zone along transportsystem 118 and/or edger infeed 122, upstream of the edger 130.Optionally, groups of sensors 120 may be positioned to form multiplesub-zones. The sensors 120 may be arranged to scan flitches traveling ina lineal orientation or in a transverse orientation.

The scanner optimizer system may further include one or more computersystems operatively coupled with the sensors 102 and 120. Each computersystem may include one or more personal computers and/or programmablelogic controllers, in any suitable number and combination.

Referring again to FIG. 1, in some embodiments the scanner optimizersystem may include first computer system 104 operatively coupled withsensors 102, and second computer system 126 operatively coupled withsensors 120. Optionally, computer system 104 and/or 126 may beoperatively coupled with a third computer system 106. Any or all of thecomputer systems may be operatively coupled with one or more laptops,tablets, netbooks, smartphones, or other portable electronic devicesused within the facility to monitor operations therein.

In some embodiments the scanner optimizer system may further include oneor more position indicator devices 124 for use to determine thepositions and/or travel speeds of workpieces on transport systems108/118. Examples of position indicator devices include, but are notlimited to, encoders (e.g., coupled with corresponding conveyors),photo-eyes, overhead cameras, and the like. The number, type, andplacement of position indicator devices may vary among embodiments.Position indicator device(s) may be used by the scanner optimizer systemto coordinate operations of the sensors, conveyor systems, cuttingdevices and other equipment, and/or data transfer among computers orcomputer systems performing the methods described herein.

In various embodiments, sensors 102 and 120 may be, or may include,laser profile sensors. Examples of suitable laser profile sensorsinclude the USNR Smart TriCam sensor with integral DSP processor framegrabber (e.g., for scanning flitches in a transverse orientation) andthe USNR LPL or LPLe sensor (e.g., for scanning flitches in a linealorientation). However, the sensors 102 and 120 may be any sensorssuitable for measuring the 3D profile of a log, a cant, or a flitch.Preferably, the sensors are configured to obtain surface measurements,filter the obtained data, and convert the obtained data to dimension(X-Y) coordinates.

In operation, a log may be conveyed on first transport system 108 in aflow direction. As the log passes through the scan zone or sub-zonesthereof, the log may be scanned by the corresponding sensors 102 tomeasure the three-dimensional profile of the log. Based on the scandata, the first computer system may generate a 3D model of the log andan optimized cut solution for the log. The first computer system mayalso generate instructions for the log turner 110, chipper 112, and saws116 to position the log, chip the log into a cant, and cut a flitch fromthe cant, respectively, according to the optimized cut solution. Theflitch may be diverted to the transport system 118, which may move theflitch in another flow direction toward edger infeed 122 while theremaining cant 116 continues along the primary breakdown line.(Typically, the remaining cant is cut into boards by a gangsawdownstream of saws 116 in accordance with the optimized cut solution.)The flitches 16 may be singulated along the transport system 118 (e.g.,by an unscrambler) before passing individually through the second scanzone to be scanned by the sensors 120 in the second scan zone. Thesecond computer system 126 may generate a 3D model of each flitch basedon the corresponding scan data. The third computer system 106 may usethe data generated by the first and second computer systems to match theflitches to the logs/cants from which they were cut, as described infurther detail below.

FIG. 2 illustrates a schematic side elevational view of a primarybreakdown line 200 a and operations of a corresponding computer system,and FIGS. 3A-3E illustrate corresponding arrangements of sensors 102and/or other sensors, all in accordance with various embodiments. In theembodiment shown in FIG. 2, the first scan zone includes multiplesub-zones formed by corresponding groups of sensors 102. The first twosub-zones are formed by sensors 102 a and 102 b, respectively, upstreamof the log turner 110. The third sub-zone is formed by sensors 102 cproximal to the log turner 110 (e.g., at or adjacent to the upstream endor downstream end of the log turner). The fourth and fifth sub-zones areformed by sensors 102 d and 102 e, respectively, between the log turner110 and the chipper 112. A sixth sub-zone is formed by sensors 102 fdownstream of saws 116. This configuration is provided by way of exampleand is not intended to be limiting. Again, the number and arrangementsof sensors and scan zones along the primary breakdown line may varyamong embodiments.

In this example, the log may be scanned by sensors 102 a and 102 b whilethe log is upstream of the log turner 110, scanned by sensors 102 cwhile being turned by the log turner, and scanned by sensors 102 d and102 e while traveling from the log turner to the chipper 112. After theflitch is sawn from the cant by saws 116, the remaining center cant maybe scanned (as a cant 14) by sensors 102 f while traveling towardanother machine center, such as a gang saw. Optionally, an additionalsub-zone may be provided between the chipper 112 and the saws 116 toscan the cant 12, or to scan the chipped faces of the cant 12, prior tosawing (see e.g., FIG. 1).

Sensors 102 a-102 f may be operatively coupled with a first computersystem (e.g., computer system 104, FIG. 1). As a log 10 is conveyedalong the primary breakdown line, the first computer system may receivescan data from the sensors 102 and analyze the scan data. The firstcomputer system may be configured to generate a 3D model of the logbased on data received from at least some of the sensors 102.Optionally, the first computer system may also be configured todetermine an optimized cut solution for the log based at least on the 3Dmodel of the log. In some embodiments the first computer system may alsobe configured to determine an optimized position for the log (e.g.,rotational position, skew angle, and/or offset). For example, the firstcomputer system may determine whether the sweep of the log exceeds apredetermined threshold; if so, the horns-down orientation may be deemedthe optimized position, and if not, the first computer system may assesspotential cut patterns in a number of positions and select the positionassociated with the greatest value of cut products as the optimizedposition.

In the configuration shown in FIG. 2, the first computer system may usescan data from the sensors 102 a and 102 b, and/or from other scannersupstream of sensors 102 a, to generate a 3D virtual model of the log anddetermine an optimized rotational position for the log. Optionally thefirst computer system may display the 3D virtual model and relatedinformation via a user interface, such as a display (e.g., userinterface 128 a). The first computer system may use data from sensors102 c to monitor the rotation of the log by the log turner and/or tosend instructions to the log turner to correct the position of the logduring/after the turn. Optionally the first computer system may displaythe log position/rotation in progress via a user interface, such as adisplay (e.g., user interface 128 b). The first computer system may usethe data from sensors 102 d and 102 e to determine an optimized cutsolution for the log. Optionally the first computer system may displaythe optimized cut solution via a user interface, such as a display(e.g., user interface 128 c).

In some embodiments, data from sensors 102 f may be used by one or morecomputer systems to monitor the performance of the primary breakdownline or parts thereof (e.g., saws 116), and/or to predict maintenancerequirements. For example, the third computer system may use the scandata from the sensors 102 f to determine geometric characteristics ofthe center cant 14 (e.g., face size, face offset, cant centerline, cantwidth, and/or cant skew) and compare the determined characteristics tocorresponding characteristics of the predicted center cant, as definedby the cut solution for the corresponding log. Optionally, thecorresponding computer system may display performance and/or maintenancedeterminations via a user interface (e.g., user interface 128 d).Likewise, if sensors 102 are arranged to form a sub-zone between thechipper 112 and the saws 116, the scan data from those sensors may beused by one or more computer systems to monitor the performance of thechipper by comparing geometric characteristics of the predicted cant andthe actual cant. In either case, the scanner optimizer system may usethe data to generate a 3D virtual model of the cant or adjust the 3Dvirtual model of the log and/or cut solution.

The number and arrangement of sensors 102 may vary among embodiments. Insome embodiments the first scan zone, or a sub-zone thereof, may includefour or five sensors 102 arranged around the path of flow, or twosensors 102 arranged above and below, or on opposite sides of, the pathof flow. In the example shown in FIG. 2, each of the first fivesub-zones includes four or five sensors 102 arranged around the path offlow (see e.g., FIGS. 3A-3C), and the sixth sub-zone includes twosensors 102 arranged on opposite sides of the path of flow (see e.g.,FIG. 3D, 3E). Again, other embodiments may have only a single scan zone,or 2-5 sub-zones, or more than six sub-zones, along the primarybreakdown line. Optionally, the first scan zone and/or one or moresub-zone(s) thereof may include one or more additional sensors 132(FIGS. 3A, 3E), which may be color vision cameras, grain angle sensors,x-ray sensors, ultrasound sensors, and/or any other type of sensor.

Along the secondary breakdown line, sensors 120 may be arranged above,below, or above and below the path of flow to form a second scan zone.Sensors 120 may be provided in any suitable number, arrangement, andorientation. If the sensors 120 are arranged for transverse scanning,sensors 120 may be spaced apart across the direction of flow (e.g., overand/or under the path of flow). FIGS. 4A-B illustrate a perspective viewand a side elevational section view, respectively, of a scanner framewith sensors 120 arranged to scan flitches that are traveling in atransverse orientation. If the sensors 120 are arranged for linealscanning, a single sensor 120 may be provided over or under a linealconveyor (e.g., edger infeed 122), or multiple sensors 120 may be spacedapart in the direction of flow and/or around the lineal conveyor.Optionally, one or more of the sensors 120 may be set at angles suchthat each of the angled sensors 120 can scan two corresponding surfacesof the flitch (e.g., a face and an edge). In some embodiments two ormore groups of sensors 120 may be positioned along the lineal conveyorat corresponding locations along the conveyor to collectively scan theflitch. In some embodiments sensors 120 may be arranged for transversescanning along transport system 118 and other sensor(s) 120 may bearranged for lineal scanning along edger infeed 122.

The first and second computer systems 104 and 126 may be configured toprocess data received from some or all of the corresponding sensors 102and 120, respectively. The first and second computer systems may be incommunication with a third computer system 106, which may be configuredto use data received from the first and second computer systems to matchthe flitches to their source logs or cants. Optionally, in someembodiments the first computer system 104 may be a conventional logoptimizer system, and the second computer system 126 may be aconventional edger optimizer system. The first computer system may beconfigured to generate a 3D model of a log and an optimized cut solutionfor the log based on scan data from the sensors 102, and the secondcomputer system may be configured to generate a 3D model of a flitchbased on scan data from the sensors 120. The third computer system maybe configured to generate a model of a predicted flitch based on the 3Dmodel of the log and the cut solution for that log, and to comparemodels of actual flitches to models of predicted flitches to therebyidentify the log/cant (and optionally, the position within the log/cant)from which the flitch was cut.

In some embodiments, the third computer system 106 may be configured todisplay visual representations of the comparisons via a user interface(e.g., a user interface 128), such as a display. Optionally, thirdcomputer system 106 may also be configured to track the matches as aqueue of log solutions and to display various parameters relevant tochipper/saw performance, such as the statistic thickness variance andwithin board deviation over a range of matches for each cutting devicecombination.

FIG. 5 illustrates a process flow for a method 300 of matching flitchesto a source primary workpiece, such as a log or a cant, with someoperations shown in further detail in FIGS. 6-10. While the blocks areshown in a particular order by way of example, it is to be understoodthat in various embodiments the corresponding actions/processes may beperformed in any order and/or any suitable number of times. Further, oneor more of the blocks may be omitted in some embodiments. Therefore, theorder and number of actions/processes is not intended to be limiting.

At block 301, a primary workpiece on transport system 108 may be scannedby geometric sensors 102. In some embodiments, the primary workpiece maybe a log (e.g., log 10), and the log may be scanned by sensors 102upstream of the chipper. Optionally, the log may be scanned in multiplesub-zones upstream of the chipper (e.g., upstream of a log turner andbetween the log turner and the chipper). In other embodiments, theprimary workpiece may be a cant (e.g., cant 12), and the cant may bescanned by sensors 102 upstream of saws 116. In still other embodiments,both the log and the corresponding cant may be scanned. Optionally, aremaining center cant (e.g., cant 16) may be scanned downstream of thesaws 116. Regardless, sensors 102 may be configured to measure the outershape of the log and to generate corresponding scan data in the form ofdimension coordinates (x, y) along the length (z axis) of the log. Inother embodiments, block 301 may be omitted (e.g., the primary workpiecemay be scanned upstream of transport system 108 or outside of thefacility, and the scan data may be transmitted to the scanner optimizersystem).

At block 303, the scanner optimizer system may generate a 3D virtualmodel of the primary workpiece based on the scan data. In someembodiments block 303 may proceed while the log 10, cant 12, and/or cant16 is transported/processed along the primary breakdown line. An exampleof a process flow for generating the 3D virtual model of the log isshown in FIG. 6.

Referring now to FIG. 6, the first computer system 104 may receive thescan data from the scanners at block 401. At block 403, based on thereceived dimension coordinates, the first computer may determine sets ofdata points (x, y coordinates) that represent the outer surface of theprimary workpiece at corresponding fixed intervals (e.g., every 4inches) along the length (z-axis) of the primary workpiece. At block405, the first computer system 104 may combine the sets of data pointsto obtain the 3D virtual model of the primary workpiece. Optionally, atblock 407 the first computer system 104 may associate the 3D virtualmodel of the primary workpiece with a corresponding log record in aqueue. In some embodiments the first computer system 104 may also createthe log record. Alternatively, another computer system (e.g., thirdcomputer system 106) may create the log record.

The method or process by which the computer system generates the 3Dvirtual model of the primary workpiece may vary among embodiments. Insome embodiments, the 3D virtual model may be generated by the computersystem as an input for determining an optimized cut solution for theprimary workpiece.

Referring again to FIG. 5, at block 305 the first computer system 104may determine an optimized cut solution for the primary workpiece basedon the scan data and/or the 3D model. The optimized cut solution maydefine the predicted products to be cut from the primary workpiece,which may include at least one predicted flitch, and the predicted cutline(s) along which the primary workpiece is to be cut to obtain thepredicted products. In some embodiments the first computer system maydetermine a saw set for positioning the saw(s) that will be used to cutthe flitch, and the saw set may be considered part of the optimized cutsolution. Optionally, the predicted cut lines may be defined by the sawset. Alternatively, the predicted cut lines may be represented by linesor planes incorporated into, or displayed relative to, the 3D model ofthe primary workpiece (see e.g., FIG. 2, user interface 128 c).

The optimized cut solution may be determined in any suitable manner. Insome embodiments, the primary workpiece may be a log, and the firstcomputer system may use the 3D virtual model of the log to determine adesired rotation angle (and optionally a desired skew/offset) for thelog. The first computer system may determine the desired rotation (andoptionally the desired skew/offset) by simulating a variety of possibleorientations for the log and selecting a ‘best’ orientation based on anyone or more of a variety of factors, such as predicted stability on adownstream conveyor (e.g., a sharp chain conveyor), a detected crack orother defect, and/or potential cut solutions that could be implemented.For example, the first computer system might simulate multipleorientations of the 3D virtual model of the log, assess the likelystability of the log on a sharp chain in each of the orientations,determine the potential cut solutions for each of the orientationsdeemed likely to be sufficiently stable on the sharp chain, and selectone of those cut solutions as the ‘optimized cut solution’ based on themonetary value of the predicted products, predicted through-put speed,and/or products needed to fill an order. In other embodiments, the firstcomputer system may determine the optimized cut solution withoutassessing predicted log stability, or based on a different combinationof factors.

In other embodiments, the primary workpiece may be a cant, and theoptimized cut solution may be determined for the cant in the same orsimilar manner as for a log. In still other embodiments the primaryworkpiece may be a cant, and the optimized cut solution may bedetermined instead (e.g., as described above) for the source log thatwas cut/chipped to form the cant.

The first computer system may communicate the optimized cut solution toa programmable logic controller (PLC) or other control device toposition the cutting devices for cutting. Again, in some embodiments thefirst computer system may generate a saw set that defines thechipper/saw position(s) for cutting the predicted flitch from theprimary workpiece, in which case the first computer system may send thesaw sets to the PLC instead of the entire optimized cut solution. Thefirst computer system may also send the 3D model of the primaryworkpiece and the cut solution to the third computer system 106. Forexample, the first computer system may associate the optimized cutsolution with the corresponding log record in the queue.

At block 307, the third computer system may generate a 3D virtual modelof the predicted flitch based at least on the 3D model of the primaryworkpiece and the cut solution. An example of a corresponding processflow 500 is illustrated in FIG. 7.

Referring now to FIG. 7, at block 501 the third computer system mayidentify the predicted cut lines that correspond to the predictedflitch. At block 503 the third computer system may identify, from the 3Dvirtual model of the primary workpiece, the data points located betweenthe two identified cut lines. At block 505, the third computer mayassociate the identified data points with the corresponding log recordas the virtual model of the flitch.

Again, in some embodiments the primary workpiece may be a log. In otherembodiments, the primary workpiece may be a cant. Regardless, thevirtual model of the predicted flitch may optionally be generated basedat least in part on geometric scan data obtained from scanning the log10, scanning the cant 12 upstream of saws 116, and/or from scanning aremaining center cant 14 downstream of saws 116.

-   -   In one embodiment the primary workpiece may be the log, and the        virtual model of the predicted flitch may be generated based on        the 3D virtual model of the log and the optimized cut solution        for the log.    -   In another embodiment the primary workpiece may be a cant (e.g.,        cant 12). The cant may be scanned by sensors 102 upstream of the        saws 116, a 3D virtual model of the cant may be generated based        on that scan data and sent to the third computer, and the third        computer may use the virtual model of the cant to generate a        virtual model of the predicted flitch (e.g., by identifying the        data points located between a chipped face of the cant and the        predicted cut line that corresponds to the other face of the        predicted flitch to be cut from that side of the cant).    -   In another embodiment, the primary workpiece may be a log.        However, the corresponding cant may be scanned by sensors 102        upstream of the saws 116 and the resulting scan data may be used        to modify the 3D virtual model of the log and/or the optimized        cut solution. For example, the width of the cant between the        chipped faces may be measured by the sensors 102, the first        computer system may determine that the measured width is        different (e.g., 0.5″ greater) than the predicted width, and the        first computer system may modify the virtual model of the log        and/or cut solution (e.g., the saw set and/or the predicted cut        lines relative to the virtual model of the log) to reflect the        actual width of the cant. The third computer system may use the        modified model/cut solution to generate the model of the        predicted flitch. Alternatively, in response to determining the        difference in width, the first computer system may determine a        corresponding offset to be applied to the 3D virtual model of        the log and/or optimized cut solution, and the third computer        system may generate the virtual model of the flitch based at        least in part on the offset (e.g., by identifying the data        points located between an outer face of the cant 12 and the        predicted cut line, as offset by the calculated distance). As        another example, the third computer system may generate a 3D        model of the cant, align the 3D model of the cant with the 3D        model of the log, and generate the virtual model of the        predicted flitch by identifying the data points between an outer        face of the cant and the predicted cut line along which the        predicted flitch is to be cut from the cant.    -   In still other embodiments, the first computer may generate a 3D        virtual model of the predicted cant based on a 3D virtual model        of the log and the optimized cut solution, and the third        computer may generate the virtual model of the predicted flitch        based on the 3D virtual model of the predicted cant (e.g., by        identifying the data points located between a face of the        predicted cant and the predicted cut line along which the        predicted flitch is to be cut from that side of the cant).    -   In yet other embodiments, after the flitch has been cut from the        cant by saws 116, the remaining center cant may be scanned by        sensors 102 downstream of the saws 116, and the third computer        may generate the virtual model of the predicted flitch based at        least on that scan data. For example, the third computer system        may generate a 3D model of the remaining center cant, align the        3D model of the remaining center cant with the 3D model of the        log or cant 12, and generate the virtual model of the predicted        flitch by identifying the data points between an outer face of        cant 12 and the corresponding outer face of the remaining center        cant. Alternatively, the third computer system may determine a        difference between the measured width of the cant 12 and/or        remaining center cant 16 and the predicted width, determine a        corresponding offset (e.g., 0.5″ in a particular direction), and        identify the data points located between an outer face of the        cant 12 and the remaining center cant 16 as offset by the        calculated distance.

Referring again to FIG. 5, at block 309 the flitch may be cut from theprimary workpiece by saws 116 according to the optimized cut solution.

At block 311 the flitch may be diverted to the secondary breakdown line(e.g., to transport system 108). At block 313, the flitch may be scannedupstream of the edger 130 (i.e., on transport system 108 and/or on edgerinfeed 122) by sensors 120. Sensors 120 may generate a plurality ofdimension coordinates that represent the shape of the actual flitch.

At block 315, the second computer system 126 may generate a 3D virtualmodel of the actual flitch. An example of a corresponding process flowis illustrated in FIG. 8.

Referring now to FIG. 8, at block 601 the second computer system 126 mayreceive the dimension coordinates for the actual flitch from sensors120. Based on the received coordinates, at block 603 the second computersystem may determine sets of data points (x, y coordinates) thatrepresent the outer surface of the actual flitch at correspondingintervals along the length (z-axis) of the flitch. At block 605 thesecond computer system may send the 3D model of the actual flitch to thethird computer 106.

Again, the method or process by which the computer system generates the3D virtual model of the actual flitch may vary among embodiments. Insome embodiments, the 3D model may be generated by the second computersystem as an input for determining an optimized cut solution for theflitch.

Referring again to FIG. 5, at block 317 the third computer system 106may compare the received 3D model of the actual flitch to 3D models ofvirtual flitches associated with log records in the queue. At block 319,the third computer system may identify the matching 3D virtual model ofthe predicted flitch based on the comparison. An example of acorresponding process flow 700 for blocks 317-319 is illustrated in FIG.9.

Referring now to FIG. 9, at block 701 the third computer system maydetermine whether a virtual model of an actual flitch has been received.The third computer system may repeat block 503 at regular intervals(e.g., every 5 seconds) until the third computer system determines thata virtual model of an actual flitch has been received.

At block 703, the third computer system may identify a first virtualmodel of the predicted flitch in the queue. In some embodiments, thequeue may be a ‘first in, first out’ (FIFO) queue, and the thirdcomputer system may identify the first model of the predicted flitch asthe one associated with the first log record in the queue. In otherembodiments, the log records and/or models of predicted flitches may bestored in a ring buffer with the log records/models for a predeterminednumber of logs, such as approximately the last 50, 100, 150, 200, 250,300, 350, 400, 450, or 500 or more logs. Optionally, the third computersystem may select the first model of the predicted flitch by selecting alog record at random, or by selecting the oldest log record that lacksan indication of a confirmed match, or by selecting the log record basedat least in part on one or more characteristics of the primary workpieceand/or cut pattern, such as a length, width, or diameter of the primaryworkpiece (or portion thereof), or a distance between saws in a saw set,or the like. For example, if the actual flitch is exactly seven feetlong, the third computer system may select the virtual model of thepredicted flitch that is nearest in length to seven feet. As anotherexample, if the maximum width of the actual flitch is twenty inches, thethird computer system may select the virtual model of the predictedflitch with a maximum width nearest to twenty inches. Alternatively, thethird computer system may select the first virtual model of a predictedflitch based on a combination of factors (e.g., the oldest log recordwith an associated model of a predicted flitch that is at least a givenlength or width, etc.)

At block 705, the third computer system may determine whether the firstvirtual model of the predicted flitch is unmatched or potentiallymatched. For example, in some embodiments the third computer system mayassume that a virtual model of a predicted flitch is unmatched orpotentially matched if a confirmed match is not indicated for that modelin the log record. Optionally, a log record may be deleted from thequeue once confirmed matches are indicated for all of the associatedmodels of predicted flitches, and the third computer system may assumethat each log record still in the queue has at least one associatedmodel that is unmatched or only potentially matched. Alternatively, onceconfirmed matches are indicated for all of the predicted flitch modelsassociated with a given log record, a corresponding indicator may beadded to the log record, and the third computer system may ignore thatlog record for the purpose of matching models of actual flitches tomodels of predicted flitches.

If the third computer system determines that the first virtual model ofthe predicted flitch is either unmatched or potentially matched, atblock 711 the third computer system may compare the model of the actualflitch to the model of the predicted flitch. In some embodiments thethird computer system may assess the similarity between the models innumeric terms to generate a similarity score. FIG. 10 illustrates anexample of a process flow for comparing the models, discussed in furtherdetail below.

At block 713, the third computer system may determine whether thesimilarity meets or exceeds a predetermined upper threshold. If thesimilarity does meet or exceed the threshold, the third computer systemmay identify the model of the actual flitch as a confirmed match to themodel of the predicted flitch (e.g., by associating the model of theactual flitch with the corresponding log record in the queue and notingthe match in the record as ‘confirmed’). The process may then return toblock 701.

However, if the similarity does not meet or exceed the threshold, thethird computer system may determine whether the similarity meets orexceeds a lower threshold (block 717). If the similarity does meet orexceed the lower threshold, the third computer system may identify themodel of the actual flitch as a potential match to the model of thepredicted flitch at block 719 (e.g., by associating the model of theactual flitch with the corresponding log record in the queue and notingthe match in the record as ‘potential’). The process may then proceed toblock 707.

Likewise, if the third computer system determines that the model of thepredicted flitch is not either unmatched or potentially matched (block705), or determines that the similarity between the models does not meetor exceed the lower threshold, the third computer system may assume thatthe model of the actual flitch is not a match to the model of thepredicted flitch, and proceed to block 707.

At block 707, the third computer system may determine whether there areany remaining models of predicted flitches in the queue. If there is atleast one other model of a predicted flitch in the queue, the processmay proceed to block 705 again to assess the next model of a predictedflitch.

If there are no other models of predicted flitches in the queue, thefirst computer system may determine whether multiple potential matcheshave been identified for the virtual model of the actual flitch. If onlyone potential match has been identified, at block 723 the third computersystem may identify the potential match as a confirmed match in thequeue (e.g., by noting the match in the corresponding log record as‘confirmed’), and the process may return to block 701.

If multiple potential matches have been identified for the virtual modelof the actual flitch, the third computer system may identify the bestpotential match and indicate the match as ‘confirmed’ in thecorresponding log record (block 725), and the process may return toblock 701. In various embodiments, the third computer system mayidentify the best match by comparing similarity scores for the matchesand selecting the highest similarity score. Optionally, any model(s) ofactual flitch(es) associated with a log record but not selected as thebest match to any model of a predicted flitch associated with that logrecord may be deleted from the log record.

The models may be compared by any suitable method. In some embodiments,the 3D virtual models of the predicted/actual flitches may be compareddirectly to one another. For example, if the log and the actual flitchare modeled as sets of coordinates uniformly spaced apart at the samefixed intervals, the 3D virtual models of the actual and predictedflitches may be compared point-by-point. Alternatively, the 3D virtualmodels may be processed for comparison to simplify or compress the datausing known techniques.

In other embodiments, 2D virtual models of the actual and predictedflitches may be generated based on the 3D virtual models of the actualand predicted flitches (or the 3D virtual models of the actual flitchand the log), and the 2D virtual models (or portions thereof) may becompared to one another. This may enable faster comparison andidentification of matches. Optionally, some or all of the 2D virtualmodels may be ‘topographical’ models. A topographical model mayrepresent the outer contour of the actual or predicted flitch within aplane that is parallel to, and at a known distance from, one or both ofthe faces defined in the 3D virtual model.

In various embodiments, a 3D virtual model of a log or flitch may begenerated as a set of cross sections at fixed intervals along the length(Z axis) of the log or flitch, with each of the cross sectionsrepresented by a corresponding set of data points. The data points maybe two-dimensional points (X and Y) that represent the outer surface atthat Z location, such that the data points collectively define the shapeof the outer surface of the log or flitch. The corresponding 2Dtopographical model may be the subset of those data points that liewithin a reference plane at a known distance from one or both faces(e.g., equidistant between the faces). Optionally, some or all of thedata points of the topographical model may be extrapolated orapproximated from the data points of the 3D virtual model (e.g., if fewor none of the data points of the 3D model are within the desiredreference plane). The location of the reference plane relative to theface(s) may be constant, such that each topographical model representsan outer contour at the same elevation. In some embodiments,topographical models may include multiple subsets of data pointsrepresenting multiple contours at corresponding fixed elevations.

FIG. 11 illustrates an example of a 3D virtual model of a flitch, invarious embodiments. As illustrated, the 3D virtual model 900 (which maybe a model of an actual flitch or a predicted flitch) may define anupper face 936 and a lower face 934 of the flitch. The 3D virtual model900 may include a plurality of data points that lie within correspondingplanes that extend between, and are parallel to, the upper and lowerfaces. In the illustrated example, data points 938 a lie within a firstplane nearest to the lower face 934, data points 938 b lie within asecond plane that is equidistant from the upper and lower faces, anddata points 938 c lie within a third plane that is nearest to the upperface 936. Thus, in this example, if the reference plane is a planeequidistant from both faces, the second plane may be considered thereference plane and the data points 938 b may collectively be consideredthe 2D topographical model. In plan view, the data points 938 b definean outer contour 940 of the flitch at the predetermined elevation(equidistant between the faces). Alternatively, a differentelevation/reference plane could be used, and the data points lyingwithin that reference plane could be considered the 2D topographicalmodel. If the 3D virtual model does not include data points within thereference plane, the computer system may extrapolate or approximate aset of data points within the reference plane from some or all of thesurrounding data points to generate the 2D model.

Referring now to FIG. 10, which illustrates a comparison and matchingmethod 800, in various embodiments the comparison and matching may beaccomplished generally as follows. At block 801 the third computer mayidentify, from a 3D virtual model of a predicted flitch, a first subsetof data points located at a first elevation relative to one or bothfaces of the predicted flitch. At block 803 the third computer mayidentify, from a 3D virtual model of an actual flitch, a second subsetof data points located at the first elevation relative to one or bothfaces of the actual flitch. In some embodiments, the identified subsetsof data points may be considered 2D models.

Optionally, the first elevation may be the elevation of a referenceplane that is halfway between, and parallel to, the faces of the flitch.For example, if a predicted flitch is three inches thick, the datapoints within a plane that is between the two faces, 1.5 inches fromeach face, may be identified as the first subset of data points.Likewise, if the actual flitch is 3.5 inches thick, the data pointswithin a plane that is between the two faces, 1.75 inches from eachface, may be identified as the second subset of data points.Alternatively, the first elevation may be a fixed elevation relative toone of the faces (e.g., 1 inch from the bottom face, or 0.5 inches fromthe upper face, etc.). As another alternative, one of the faces may bethe reference plane (e.g., an elevation of zero relative to that face).However, using a reference plane located between the planes of the facesmay help to reduce or avoid mismatches caused by damage to the wane edgealong the lower face and/or inaccurate detection of the wane edge alongthe upper face.

At block 805, the third computer system may compare data points from thefirst subset to corresponding data points of the second subset. In someembodiments, the computer system may identify the data points in eachsubset that correspond to a given z location and compare those datapoints. For example, each 2D model may have two data points for each zlocation (one for each wane edge). Because the data points of a subsetlie within a single plane (e.g., the plane of x), one of the coordinates(e.g., x) may be the same for each data point of that subset. Thus, fora given z location, the computer system may compare the numeric valuesof the remaining coordinate (e.g., the y values). Optionally, one of thenumeric values may be negative and the other may be positive (e.g., leftof centerline is negative and right of centerline is positive, or viceversa) and the computer system may compare negative values to negativevalues and positive values to positive values. Alternatively, thecomputer system may sum each pair of data points and compare the sumsfor that z location.

In some embodiments, comparing the 2D models may involve aligning themodels for comparison. The computer system may try to align one model tothe other in multiple orientations (e.g., by rotating the model and/orflipping the model vertically or horizontally), either randomly or in aparticular order, and select the orientation that provides the bestalignment/highest similarity. Alternatively, the computer system may useknown orientation factors, such as the orientation of the log along theprimary breakdown line (i.e., large end leading, or small end leading)and/or the orientation of the edger and direction of travel of flitchesto the edger to determine which edges correspond to one another. Forexample, if the logs are moved and scanned along the primary breakdownline with the smaller end of the log upstream of the larger end, thefirst (z) interval of the 3D log models may correspond to the smallerend of the log, and the first (z) interval of the 3D model of thepredicted flitch may likewise represent the end of the flitch cut fromthe smaller end of the log. If the flitches are diverted onto thetransport system 118 in the same orientation in which they were cut fromthe log, and they are scanned in the transverse orientation with thewane side up, the first (z) interval of the 3D model of the actualflitch may be assumed to be at the end of the flitch that corresponds tothe small end of the log.

Optionally, after comparing the data points at the first elevation(i.e., comparing the contours of the two models at a single elevation),the third computer system may compare contours at one or more additionalelevations. For example, if the contours at the first elevation do notmatch within a predetermined tolerance, the contour of the actual flitchat the first elevation may be compared to another contour of thepredicted flitch at a different elevation, and/or another contour of theactual flitch at a different elevation may be compared to the contour ofthe predicted flitch at the first elevation or a different elevation.Alternatively, if the contours at the first elevation match within thepredetermined tolerance, one or more additional contours may be comparedto further assess and/or confirm the match. Although FIG. 11 illustratesthree distinct elevations, one of skill in the art will appreciate thatany number of elevations may be selected and compared as a part of thematching process. Optionally, a suitable tolerance can be selected bydetermining a range of variation for known matches (e.g., by aligningcontours of actual and predicted flitches known to be matches) andchoosing a tolerance that accommodates that range, and optionally onethat accommodates a slightly greater range of variation.

In some embodiments, a length offset may be applied in the matchingprocess. This may help to identify matches where the actual flitch isslightly longer or shorter than the predicted flitch, which may occur asthe result of inaccurate cutting, damage to the actual flitch upstreamof the sensors 120, inaccurate position data from an encoder or otherposition indicator along the primary breakdown line, or other causes.Therefore, a contour of the predicted flitch at the first elevation maybe compared to a contour of the actual flitch at the same elevation,with both contours aligned along the z axis (e.g., by comparing the datapoints at the first z location of one model to the data points at thefirst z location of the other model, and so on). If the contours do notmatch within the predetermined tolerance, the contours may be comparedagain with one of the contours offset relative to the other along the zaxis (e.g., by comparing the data points at the first z location of onemodel to the data points at the second z location of the other model).Optionally, comparisons may be made in a similar fashion with lengthoffsets in one or both directions up to a predetermined number ofdistance increments.

In various embodiments, an elevation offset contour alignment may beperformed. When the log line is cutting correctly, the best matches aretypically identified by comparing contours at the same elevation.However, cutting offset errors may reduce the number of matchesidentified by that method. Although detecting a reduction in matches mayhelp to detect a cutting offset problem, the reduction in matches maymake the determination of a correction factor more challenging.Therefore, a contour of the predicted flitch at the first elevation maybe compared to a contour of the actual flitch at the first elevation,and this process may be repeated by comparing one of the contours (e.g.,the contour of the actual flitch at the first elevation) to the contoursof the other model that are one or more increments above and/or belowthe first elevation. For example, if the elevations are at intervals of2/10 of an inch, and the first elevation is at 0.2 inches from thebottom face, the contours of both models at 0.2 inches from the bottomface may be compared, and the contour of one model at 0.2 inches fromthe bottom face may be compared to contours of the other model at 0.4,0.6, and 0.8 inches from the bottom face. Alternatively, contours of onemodel can be compared to contours of the other model offset by anincrement of elevation, such as by comparing the predicted contour at anelevation of 0.4 inches to the actual contour at 0.2 inches, comparingthe predicted contour at 0.6 inches to the actual contour at 0.4 inches,and comparing the predicted contour at 0.8 inches to the actual contourat 0.6 inches, etc., or vice versa. Optionally, the inverse of thisprocess may also be performed, such as by comparing the actual contourat an elevation of 0.4 inches to the predicted contour at 0.2 inches,comparing the actual contour at 0.6 inches to the predicted contour at0.4 inches, etc.

Optionally, after aligning a pair of contours, the computer system mayapply the offset(s) (if any) to one or more additional contours of thetwo models and compare the additional contour(s). Alternatively, thecomputer system may compare only one contour from each model (e.g., bycomparing the 2d models).

At block 807, the computer system may determine a similarity score basedon the comparison. In some embodiments, the computer system maydetermine alignment deviation values (e.g., deviation betweencorresponding data points at each z location) and use the alignmentdeviation values to determine the similarity score. For example, if thecomputer system aligns only one contour of the two models (e.g., byaligning the 2D models), the computer system may determine an alignmentdeviation value at each z location and the similarity score may be thesum of the alignment deviation values. As another example, if thecomputer system aligns multiple contours of two models, the computersystem may determine alignment deviation values at each correspondingelevation, and the similarity score may be the sum of the alignmentdeviation values and their variance between contours. Alternatively, thecomputer system may calculate the similarity score by averaging thealignment deviation values, discarding or disregarding any alignmentdeviation values that are above or below a threshold value, and/orcalculate the similarity score in some other manner. Regardless, thecomputer system may record the similarity score in the corresponding logrecord. In the event that the alignment of the models/contours includeda longitudinal offset and/or elevational offset, the computer system mayalso record the offset(s) in the corresponding log record.

Optionally, the computer system may be configured to display thecomparisons and/or matches via a user interface (e.g., a user interface128), such as a display. The computer system may also be configured totrack the matches as a queue of log solutions.

FIG. 14 illustrates an example of a user interface screen 1252 fordisplaying match results, in accordance with various embodiments. Userinterface screen 1252 may include an alignment window 1254, one or morematch analysis windows 1256, and/or a match ranking window 1258.

The computer system may display a visual representation of a model of apredicted flitch aligned with a model of an actual flitch in thealignment window 1254. In some embodiments the models may be 2Dtopographical models. As discussed above, the models of the predictedflitches may be associated with corresponding logs in a log queue. Forexample, in the illustrated alignment window, a 2D topographical modelof a predicted flitch (designated as “57”) for a particular log (“Log4239_1”) is shown aligned with a 2D topographical model of an actualflitch (designated as “flitch 0_0(2) L5532.3”). Optionally, in someembodiments the model of the actual flitch may be aligned with acorrected model of the predicted flitch (designated in FIG. 14 as “logcorrection”) instead of, or in addition to, the original model of thepredicted flitch. For example, cants may be scanned between the chipperand the saws to determine the dimensions and relative locations of thechipped faces, and that data may be used to adjust the correspondingmodels of the predicted flitches to obtain the corrected models. The useof corrected models of predicted flitches may help to reduce the impactof inaccurate chipping on the speed and accuracy of the matchingprocess, by adjusting for the inaccuracy before the comparison. In otherembodiments, corrected models may not be generated, and the computersystem may use only the original models of the predicted flitches andthe models of the actual flitches for the comparison and matching.

The computer system may display various analysis parameters (e.g.,differences in length/thickness, similarity scores, offsets, etc.),and/or indicate the result of the comparison (e.g., as a valid match, apotential match, or no match), in match analysis window(s) 1256. Forexample, in the illustrated match analysis window on the left, thefourth line of text indicates that the compared models are a validmatch. Optionally, the computer system may provide an overall matchscore. In the illustrated example, the overall match score (designatedas “OAMatch”) for the model of the predicted flitch 57 is 6.7.

The computer system may display a list of other valid and/or potentialmatches for that model in match ranking window 1258. Optionally, theother valid/potential matches may be ranked based on the respectiveoverall match scores and/or other analysis parameters. As eachcomparison is made, the result of the comparison may be added to thelist. For example, in the illustration of FIG. 14, if the overall matchscore of 6.7 for the model of the predicted flitch 57 is higher than theoverall match score for the first model on the list, the model of thepredicted flitch 57 will be added to the top of the list, and theprevious best match will become the second one on the list. If theoverall match score for the model of the predicted flitch 57 is lowerthan the overall match score for the first model on the list, but betterthan the overall match score for the second model on the list, the modelof the predicted flitch 57 will be inserted into the list between thefirst and second models. The computer system may compare the model ofthe actual flitch to additional models of predicted flitches and modifythe list accordingly.

In some embodiments, the computer system may display comparison andmatch results for the predicted cut products (e.g., cants and flitches)of multiple logs in real time. For example, the computer system maydisplay a list of log identifiers for at least some of the logs in thequeue, the corresponding cut products, and information about whethereach of the corresponding cants and flitches has been matched.Optionally, the computer system may also display an indication of thecutting members (e.g., chip head and saw, or pair of saws) used to cuteach of the cants and flitches. FIG. 15 illustrates an example of acorresponding user interface screen 1260. In this figure, logs areidentified by number in the left column. The remaining columnscorrespond to nine zones (Left Zones 1-4, Cant, and Right Zones 4-1),with each zone representing one or more combinations of cutting members.Cut products for each log are indicated in the respective columns. Forexample, outer flitches/boards cut from the log by the left chipper (LC)and one of the saws (L[saw number]) are listed in Left Zone 1;flitches/boards cut from the log by the first saw (L1) and one of theother saws are listed in Left Zone 2; and so on. As each model of anactual flitch is matched to a model of a predicted flitch, thecorresponding entry in the columns is highlighted to indicate the match.Final matches may be differentiated from non-final or potential matchesby color or in any other suitable manner. For instance, in FIG. 15, allof the products in Right Zone 1 have been finally matched except for thefirst and sixth entries on the list (no matches) and the ninth(potential match identified, but not finally matched).

User interfaces can be configured to display comparison and matchinformation in any suitable manner. The arrangement, content, and formatof the user interface screen(s) may vary widely among embodiments, andthose variations will be readily apparent to those skilled in the art.User interface screens may also be used in some embodiments to displayadditional information about other parameters, such as product thicknessand cutting accuracy, and discussed in further detail below. Referringagain to FIG. 5, after matching a model of an actual flitch with a modelof a predicted flitch, the third computer system may optionally assessone or more differences (e.g., in thickness, length, width,wane/contour, and/or corresponding zone of source workpiece) between thepredicted flitch and the actual flitch (block 321). In some embodimentsat block 323 the third computer system may also adjust a saw, generatean alert or error message, or adjust another component of theprimary/secondary breakdown line based on the difference(s). The thirdcomputer system may also determine which of the saws was used to cuteach flitch, either at block 321 or elsewhere in the process flow (e.g.,at block 323).

A corresponding process flow 1000 is shown in FIG. 12, and correspondinguser interface screens are shown in FIGS. 16-17, in accordance withvarious embodiments.

At block 1001, the computer system may determine a predicted thicknessof a flitch based on the virtual model of the predicted flitch. At block1003, the computer system may determine an actual thickness of theflitch based on the virtual model of the actual flitch and/orcorresponding data from the sensors 120. In some embodiments thecomputer system may determine the actual thickness at multiple locationsalong the length of the flitch.

At block 1005, the computer system may determine a difference betweenthe predicted thickness and the actual thickness.

In some embodiments, the computer system may display the predicted andactual thicknesses, and/or the difference between them. FIG. 16illustrates an example of a corresponding user interface screen 1270.This user interface screen may be a more detailed version of userinterface screen 1260, and both screens may have corresponding buttonsthat allow the user to switch back and forth between the views. Inresponse to user selection of an entry that has been matched, thecomputer system may display information about the thickness of theactual flitch and the deviation from the predicted/desired thickness inthickness window 1280. In this example, thickness window 1280 indicatesthe thickness of the actual flitch at increments along the length of theflitch and the deviation of the actual thickness from thedesired/predicted thickness (“Target Thickness”) at each of thoseincrements.

At block 1007, the computer system may compare the difference to athreshold value. For example, a threshold value may be set based on arange of differences between actual and predicted thicknesses observedwithin a given time period during which the saws and other equipment arebelieved to be correctly calibrated and performing as desired.

At block 1009, the computer system may determine differences betweenpredicted and actual thicknesses of additional flitches cut by the samesaw. The computer system may also determine differences betweenpredicted and actual thicknesses of flitches cut by other saws, and/ordifferences between other predicted and actualparameters/characteristics.

At block 1011, the computer system may compare the differences for agiven saw with differences for another saw, such as an adjacent saw. At1031, the computer system may generate an instruction or recommendationfor adjusting one or more of the saws, and/or other equipment, based onthe comparison. The computer system may also cause the adjustment (e.g.,by sending the instruction to a PLC) instead of, or in addition to,generating the recommendation or instruction.

In various embodiments, the computer system may track detecteddifferences between the predicted flitches and actual flitches incombination with other information, such as the saw(s) used to cut theflitches, the order in which the flitches were cut by the particularsaw(s), cutting/transport speed, and/or other features orcharacteristics. For example, if the third computer system determinesthat successive flitches cut by the outermost right saw are consistently0.1″ thinner than predicted, the third computer system may generate arecommendation to reposition the outermost right saw by 0.1″ to offsetthe positional error, and/or generate and send an instruction to acorresponding PLC to implement that correction. As another example, ifthe third computer system determines that successive flitches cut by theoutermost right saw at a given transport speed are not being cut at aconsistent thickness (e.g., thickness varies along the length of theflitch), the third computer system may conclude that the correspondingsaw is snaking and generate recommendations for the operator, and/orgenerate and send instructions to the PLC, to adjust the saw tensionand/or perform other maintenance/repair on the saw. In contract, if thethird computer system determines that flitches cut by multiple saws atan increased speed are not being cut at a constant thickness, the thirdcomputer system may generate recommendations for the operator and/orgenerate and send instructions to the PLC, to reduce the speed of thecorresponding workpiece transport.

In some embodiments, the scanner optimizer system includes sensorspositioned to scan the cant upstream of saws 116 and/or the remainingcenter cant downstream of saws 116, and the third computer system mayuse the corresponding scan data in combination with other data tomonitor operational parameters of the primary breakdown line. Thescanner optimizer system may compare predicted and actualcharacteristics of cant 14 and/or cant 16 such as left face size, leftface offset, right face size, right face offset, cant centerline, cantwidth, and/or cant skew. For example, if the scanner optimizer systemdetermines that the size of the left face of successive cants 14 isconsistently larger or smaller than predicted, or is consistently offsetby 0.2″ from the expected position, the scanner optimizer system mayconclude that the logs are not being positioned correctly upstream ofthe chipper (e.g., if the actual cant width matches the predictedwidth), or that the left chip head is not being positioned correctly tochip the left side of the logs (e.g., if the actual cant width does notmatch the predicted cant width).

In some embodiments, the computer system (e.g., third computer systemand/or scanner optimizer system) may display thickness deviations,recommendations for adjusting the chippers/saws, and/or otherparameters. For example, the computer system may track the thickness (orthickness deviations) of the cants and flitches over time, displayvisual representations of the thickness deviations relative to thecorresponding cutting members (e.g., chippers and saws), and displayrecommended adjustments to each of the cutting members. Optionally, thecomputer system may display a user-selectable button or other suchfeature that causes the computer system to implement the recommendedadjustment(s). FIG. 17 illustrates an example of a corresponding userinterface screen 1280. This user interface screen indicates the leftchipper (“L Chip”), right chipper (“R Chip”), and four saws (5-9)downstream of the chipper, which collectively are used to cut a leftouter flitch (LO), a left inner flitch (LI), center cant (cant), rightinner flitch (RI), and right outer flitch (RO), from a log. In thisexample, for each of the products, the computer system displays arepresentation of the thickness deviations 1284 and an average thicknessdeviation 1286, and for each of the cutting members the computer systemdisplays a recommended adjustment 1288 and a predicted average thicknessdeviation 1290 (the average thickness deviation predicted for thecutting member if the recommended adjustment were implemented). The userinterface screen may also have a button 1292 that is selectable by theuser to cause the computer system to implement the recommendedadjustment(s).

Although the present disclosure describes a scanner optimizer systemwith three computer systems performing corresponding operations, thosewith ordinary skill in the art will readily appreciate that theoperations may instead be performed by a single computer system, ordistributed in other ways among multiple computer systems. For example,in some embodiments the first and second computer systems may generate2D models of the predicted and actual flitches, respectively, or thefirst or second computer system may generate the 2D models. Likewise, insome embodiments the first computer system may include multiplecomputers, and the operations of the first computer system may bedistributed among the computers (e.g., one computer generates the 3Dmodel of the log, another computer determines the optimized rotationalposition, and a third computer determines the optimized cut solution).Still other embodiments may have only one computer system that performsall of the operations attributed herein to the first, second, and thirdcomputer systems. In some embodiments a computer system and some of thecorresponding sensors may be integrated within a common housing, or maybe separate components operatively connected.

FIG. 13 illustrates an example of a computer system 1150 suitable forperforming some or all of the operations/methods described herein, inaccordance with various embodiments. Computer system 1150 may have someor all of the features described herein with regard to various computersystems (e.g., first computer system 104, second computer system 126,and/or third computer system 106).

As illustrated, computer system 1150 may include system control logic1158 coupled to at least one of the processor(s) 1154, memory 1162coupled to system control logic 1158, non-volatile memory (NVM)/storage1166 coupled to system control logic 1158, and one or morecommunications interface(s) 1170 coupled to system control logic 1158.In various embodiments, system control logic 1158 may be operativelycoupled with sensors (e.g., sensors 102, 120, and/or 132) and/or anoutput device (e.g., user interfaces 128 a-d). In various embodimentsthe processor(s) 1154 may be a processor core.

System control logic 1158 may include any suitable interfacecontroller(s) to provide for any suitable interface to at least one ofthe processor(s) 1154 and/or any suitable device or component incommunication with system control logic 1158. System control logic 1158may also interoperate with the sensors and/or the output device(s). Invarious embodiments, the output device may include a display.

System control logic 1158 may include one or more memory controller(s)to provide an interface to memory 1162. Memory 1162 may be used to loadand store data and/or instructions, for example, for various operationsof lumber processing system 100. In one embodiment, system memory 1162may include any suitable volatile memory, such as suitable dynamicrandom access memory (“DRAM”).

System control logic 1158, in one embodiment, may include one or moreinput/output (“I/O”) controller(s) to provide an interface toNVM/storage 1166 and communications interface(s) 1170.

NVM/storage 1166 may be used to store data and/or instructions, forexample. NVM/storage 1166 may include any suitable non-volatile memory,such as flash memory, for example, and/or any suitable non-volatilestorage device(s), such as one or more hard disk drive(s) (“HDD(s)”),one or more solid-state drive(s), one or more compact disc (“CD”)drive(s), and/or one or more digital versatile disc (“DVD”) drive(s),for example.

The NVM/storage 1166 may include a storage resource that may physicallybe a part of a device on which computer system 1150 is installed, or itmay be accessible by, but not necessarily a part of, the device. Forexample, the NVM/storage 1166 may be accessed over a network via thecommunications interface(s) 1170.

System memory 1162, NVM/storage 1166, and/or system control logic 1158may include, in particular, temporal and persistent copies of workpieceprocessing logic 1174. The workpiece processing logic 1174 may includeinstructions operable, upon execution by at least one of theprocessor(s) 1154, to cause computer system 1150 to practice one or moreaspects of operations described herein (e.g., creation of a 3D virtualmodel of a log, cant, and/or flitch based on sensor data, calculation ofa cut solution, creation of a 3D virtual model of a predicted flitch,creation of 2D virtual models of predicted and actual flitches,comparison of virtual models, identifying a source log/cant based on thecomparison, monitoring and analyzing performance of saws and otherequipment, adjusting positions or operations of saws and otherequipment, displaying comparison and match information/results,displaying performance analysis information/results, etc.)

Communications interface(s) 1170 may provide an interface for computersystem 1150 to communicate over one or more network(s) and/or with anyother suitable device. Communications interface(s) 1170 may include anysuitable hardware and/or firmware, such as a network adapter, one ormore antennas, a wireless interface, and so forth. In variousembodiments, communication interface(s) 1170 may include an interfacefor computer system 1150 to use NFC, optical communications (e.g.,barcodes), BlueTooth or other similar technologies to communicatedirectly (e.g., without an intermediary) with another device. In variousembodiments, the wireless interface may interoperate with radiocommunications technologies such as, for example, WCDMA, GSM, LTE, andthe like.

The capabilities and/or performance characteristics of processors 1154,memory 1162, and so forth may vary. In various embodiments, computersystem 1150 may include, but is not limited to, a smart phone, acomputing tablet, a laptop computer, a desktop computer, and/or aserver. In various embodiments computer system 1150 may be, but is notlimited to, one or more servers known in the art.

In one embodiment, at least one of the processor(s) 1154 may be packagedtogether with system control logic 1158 and/or workpiece processinglogic 1174. For example, at least one of the processor(s) 1154 may bepackaged together with system control logic 1158 and/or workpieceprocessing logic 1174 to form a System in Package (“SiP”). In anotherembodiment, at least one of the processor(s) 1154 may be integrated onthe same die with system control logic 1158 and/or positioning logic.For example, at least one of the processor(s) 1154 may be integrated onthe same die with system control logic 1158 and/or positioning logic toform a System on Chip (“SoC”).

The computer system may be configured to perform any or all of thecalculations, operations, and/or functions described above and/or inFIGS. 5-10 and 12.

Thus, in various embodiments, a virtual model of a predicted flitch maybe aligned with virtual models of actual flitches to identify a sourceworkpiece, such as a log or a cant, from which the actual flitch wascut, as well as the corresponding zone of the source workpiece. This mayenable identification of the saw(s) used to cut the flitch from theprimary workpiece, allowing the operator to detect and address amisalignment or operational error of the saw(s) or other equipment. Inaddition, identifying the source workpiece may enable identification ofthe species of each flitch upstream of the edger, which may allow theoperator and/or computer system to determine or adjust a cut solutionfor the flitch based at least in part on the wood species.

Although certain embodiments have been illustrated and described herein,it will be appreciated by those of ordinary skill in the art that a widevariety of alternate and/or equivalent embodiments or implementationscalculated to achieve the same purposes may be substituted for theembodiments shown and described without departing from the scope. Thosewith skill in the art will readily appreciate that embodiments may beimplemented in a very wide variety of ways. This application is intendedto cover any adaptations or variations of the embodiments discussedherein. Therefore, it is manifestly intended that embodiments be limitedonly by the claims and the equivalents thereof.

What is claimed is:
 1. A computer-readable medium comprising instructions operable, upon execution by a processor, to generate, based at least on a 3D model of a primary workpiece and a cut solution for the primary workpiece, a virtual model of a predicted flitch, compare a virtual model of an actual flitch to the virtual model of the predicted flitch, and based on the comparison, identify the primary workpiece as the source of the actual flitch.
 2. The computer-readable medium of claim 1, wherein said virtual models are 3D virtual models, and the instructions are further operable, upon execution by the processor, to determine, based at least on the 3D model of the predicted flitch, a first group of data points that represent an outer contour of the predicted flitch at a first elevation relative to a first face of the predicted flitch, and determine, based at least on the 3D model of the actual flitch, a second group of data points that represent outer contour of the actual flitch at said first elevation relative to a corresponding first face of the predicted flitch, and compare the data points of the first group to the corresponding data points of the second group to thereby compare the virtual model of the actual flitch to the virtual model of the predicted flitch.
 3. The computer-readable medium of claim 2, wherein the first elevation is an elevation equidistant between the first face and an opposite second face of one of said flitches.
 4. The computer-readable medium of claim 1, the instruction further operable, upon execution by the processor, to generate, based at least on a 3D virtual model of a second primary workpiece and a cut solution for the second primary workpiece, a second virtual model of a second predicted flitch compare the virtual model of the actual flitch to the second virtual model of the second predicted flitch, and based on the comparison, eliminate the second primary workpiece as the source of the actual flitch.
 5. The computer-readable medium of claim 2, wherein the primary workpiece is a log.
 6. The computer-readable medium of claim 2, wherein the primary workpiece is a cant.
 7. A system for identifying a primary workpiece as the source of a flitch, the system comprising: a first scanner optimizer system including a plurality of first sensors operatively coupled with a first computer system, wherein the first sensors are collectively positioned to scan a primary workpiece along a first path of flow and operable to measure a geometric profile of the primary workpiece, and the first computer system is configured to generate a virtual model of the primary workpiece and a cut solution for the primary workpiece based at least on data from the first sensors; a second scanner optimizer system including a plurality of second sensors operatively coupled with a second computer system, wherein the second sensors are collectively positioned to scan a flitch along a second path of flow and operable to measure a geometric profile of the flitch, and the second computer system is configured to generate a virtual model of the flitch based at least on data from the second sensors; and a third computer system operatively coupled with the first and second computer systems and programmed with instructions operable, upon execution, to generate a virtual model of a predicted flitch based at least on the virtual model of the primary workpiece and the cut solution, compare the virtual model of the flitch to the virtual model of the predicted flitch, and based on the comparison, identify the primary workpieces as the source of the flitch.
 8. The system of claim 7, wherein the virtual model of the predicted flitch and the virtual model of the flitch are 3D models, and the instructions are further operable, upon execution, to determine a first group of data points that represent the outer contour of the predicted flitch at a first elevation relative to a first face of the predicted flitch, determine a second group of data points that represent the outer contour of the flitch at the first elevation relative to a corresponding first face of the flitch, and compare the virtual model of the flitch to the virtual model of the predicted flitch by comparing the first group of data points to the second group of data points.
 9. A method of matching a flitch to a source log, the method comprising: detecting a geometric profile of a primary workpiece with a first plurality of sensors; generating a virtual model of the primary workpiece and a cut solution for the primary workpiece based at least on the detected geometric profile of the primary workpiece; generating a virtual model of a predicted flitch based at least on the virtual model of the primary workpiece and the cut solution; detecting a geometric profile of a flitch; generating a virtual model of the flitch based at least on the detected geometric profile of the flitch; comparing the virtual model of the predicted flitch to the virtual model of the flitch; and based on the comparison, identifying the primary workpiece as the source of the flitch.
 10. The method of claim 9, wherein comparing the virtual model of the predicted flitch to the virtual model of the flitch includes determining a first outer contour of the predicted flitch at a first elevation relative to a first face of the predicted flitch, determining a second outer contour of the flitch at said first elevation relative to a corresponding first face of the flitch, and comparing the first outer contour to the second outer contour.
 11. The method of claim 10, wherein the first outer contour is represented by a group of first coordinates at intervals along a length of the predicted flitch, and the second outer contour is represented by a group of second coordinates at intervals along a length of the flitch, and wherein comparing the first outer contour to the second outer contour includes comparing the first coordinates to corresponding ones of the second coordinates.
 12. The method of claim 9, further comprising identifying a zone within the primary workpiece as the zone from which the flitch was cut, based at least in part on the cut solution.
 13. The method of claim 12, further comprising identifying, based at least on the identified zone or the cut solution, a saw that was used to cut the flitch from the primary workpiece.
 14. The method of claim 13, further comprising: determining one or more geometric differences between the predicted flitch and the flitch, and adjusting a position of said saw based at least on the one or more geometric differences.
 15. A method of modifying a log processing system, wherein the log processing system includes a first scanner optimizer and a second scanner optimizer, the method comprising: operatively coupling a computer system with the first and second scanner optimizers, wherein the computer system is programmed with instructions operable, upon execution, to: receive a virtual model of a primary workpiece and a cut solution for the primary workpiece from the first scanner optimizer, generate a virtual model of a predicted flitch based at least on the virtual model of a primary workpiece and the cut solution; receive a virtual model of an actual flitch from the second scanner optimizer; compare the virtual model of the predicted flitch to the virtual model of the actual flitch; and identify the primary workpiece as the source of the flitch based at least on the comparison.
 16. The method of claim 15, wherein comparing the virtual model of the predicted flitch to virtual model of the actual flitch includes comparing an outer contour of the predicted flitch at a first elevation relative to a first face of the predicted flitch to an outer contour of the actual flitch at a corresponding elevation relative to a corresponding face of the actual flitch.
 17. The method of claim 16, wherein each of the contours is represented by a plurality of coordinates that lie within a plane at said first elevation, and wherein comparing the contours includes comparing the coordinates of each contour at respective locations along a longitudinal axis of the contours.
 18. The method of claim 17, wherein the first elevation does not coincide with the first face or an opposite second face of the predicted flitch or the actual flitch.
 19. The method of claim 16, further including identifying a saw used to cut the actual flitch, based at least on the cut pattern.
 20. The method of claim 17, further including determining a first geometric difference between the actual flitch and the predicted flitch, and based on the first geometric difference, adjusting a position of the saw.
 21. The method of claim 15, wherein the instructions are further operable, upon execution, to: compare a virtual model of a second predicted flitch to the virtual model of the actual flitch; and identify the virtual model of the second predicted flitch as a potential match to the virtual model of the actual flitch based on the comparison. 